PROJECT SUMMARY/ABSTRACT Across all cancers a significant problem in oncology is the current lack of reliable means to predict response to anti-cancer treatments for individual patients. Specifically in locally advanced rectal cancer (LARC), it is known that patients can benefit from chemotherapy, radiation, and operative management. However, not all of these therapies may be required for each individual patient. Beyond that for patients with metastatic colorectal cancer (CRC) multiple standard and experimental therapies exist and a way to predict which patients will respond to which therapies would be a major advance. Sensitivity testing would prevent patients from unnecessarytoxicities and allow escalation of or alternative therapies for those with resistant disease. A method to predict treatment response is urgently needed and this is the goal of this proposal. The long-termobjective of this proposal is to utilize optical metabolic imaging (OMI) of patient-derived CRC spheroid cultures to predict sensitivity to therapeutic regimens. This proposal develops novel cellular-level imaging technologies to predict treatment response in individual cancer patients using optical metabolic imaging (OMI) of spheroid cultures from their own tumors. Since tumor genetics can have profound impacts on cellular metabolism, a better understanding of the underlying mechanisms by which tumor genetics alter OMI in the pre- and post-treatment settings is needed. In addition, assessment of cell-level heterogeneity within patient samples is required to fully predict the treatment response. To interrogate these mechanistic inquiries, we have generated multiple tools including transgenic murine CRC models possessing combinations of mutations in commonly altered genes, murine CRC spheroid cultures, isogenic human CRC cells, and patient-derived spheroid cultures and xenografts. Our preliminary data indicate that OMI in primary CRCs and other tumor types predicts in vivo drug response in mice. We have also tested this platform in pilot studies using patient-derived CRC spheroids. In this proposal, we test the hypothesis that OMI of patient-derived spheroid cultures will predict treatment response for patients undergoing chemotherapy and/or radiation for CRC. Specifically, we determine how individual genetic alterations within spheroids impact OMI pre- and post-treatment with chemotherapy and/or radiation. Secondly, we evaluate the heterogeneity within CRC spheroid cultures with complex molecular profiles using OMI pre- and post-treatment with chemotherapy and/or radiation. In addition, we test whether spheroid response using OMI predicts clinical responsein patients undergoing neoadjuvant treatment for locally advanced rectal cancer and for systemic therapies for patients with metastatic CRC. Patients will be enrolled in a registry protocol prior to the initiation of therapy. The OMI predictions will be validated with the clinical outcomes based on pathology and imaging criteria.